<i>Out of Sorts: On Typography and Print Culture</i> . By J <scp>oseph</scp> A. D <scp>ane</scp> . <i>Out of Sorts: On Typography and Print Culture</i> . By DaneJoseph A.. Philadelphia: University of Pennsylvania Press. 2010. 240 pp. £30. <scp>isbn</scp> 978 0 8122 4294 2.
Bibliographic record
Abstract
Joseph Dane continues his sceptical evaluation of the philosophical nature of ‘facts’ and ‘evidence’ that he previously discussed in detail in The Myth of Print Culture (Toronto: University of Toronto Press, 2003) and Abstractions of Evidence (Farnham: Ashgate, 2009). Criticizing David Bradshaw's assertion that facts tell their own story, without the need for rigorous and detailed interpretation, Dane here offers an exposition of so-called bibliographical ‘grand narratives’, or models of thinking about bibliography that, Dane argues, obscure what the actual evidence might tell us. Sometimes, as Dane shows, the comparison between repeated grand narratives and looking hard at the evidence can produce some startling differences. Such post-structuralist viewpoints are often criticised for maligning what we have come to accept as a given; yet such studies can and will serve as important reminders to bibliographers and book historians alike that evidence should be prioritized over predefined assumptions of critical interpretation. The trick, perhaps, is to report these new readings in ways that are meaningful and incontrovertible.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.009 | 0.019 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.032 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".